| W. Elwasif, J. Plank, R. Wolski. Data Staging Effects in Wide Area Task Farming Applications. IEEE International Symposium on Cluster Computing and the grid, pp. 122-129, May 2001, |
....that the network transfer times are negligible because we are dealing with applications that have small input output data. This means either that the tasks are CPU bound or that large amounts of data have been previously staged in the grid, as it is common practice for data grid applications [5] [15] Another point that has to be emphasized about our experiments is that the information based algorithms (Dynamic FPLTF and Sufferage) are fed with perfect data about machines and tasks, something that is almost impossible in the real world. All experiments have a fixed value for grid power ....
W. Elwasif, J. Plank and R. Wolski. Data Staging Effects in Wide Area Task Farming Applications. IEEE International Symposium on Cluster Computing and the grid, Brisbane, Australia, May, 2001, pp. 122-129.
....assumption we make for our work is that the transfer times are negligible because we are dealing with small input output data. This means either that the tasks are CPU bound or that large amounts of data have been previously staged in the Grid, as it is common practice for data grid applications [4, 13]. Each experiment has a number of machines between 100 and 500 which is randomly picked using a uniform distribution, denoted by U(100, 500) It is known that the speed of the machines practically duplicates every year, so to simulate the heterogeneity of the machines in up to 5 years we used the ....
W. Elwasif, J. Plank, and R. Wolski. Data staging effects in wide area task farming applications.
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W. Elwasif, J. Plank, R. Wolski. Data Staging Effects in Wide Area Task Farming Applications. IEEE International Symposium on Cluster Computing and the grid, pp. 122-129, May 2001,
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